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热词推荐: 基础设施能源

中国海洋清洁能源发展分析与预测

文章摘要

21世纪以来,海上风电、海上光伏和海洋天然气等海洋清洁能源的开发和利用取得显著进展,成为能源绿色转型的关键力量。然而,目前海洋清洁能源发展也面临着诸多机遇与挑战。技术瓶颈、环境影响以及资源可持续利用等问题限制了其进一步发展。在此背景下,对中国海洋清洁能源发展进行分析与预测具有重要意义。本报告对海洋清洁能源发展背景与现状进行梳理,建立集成模型对中国主要海洋清洁能源的未来发展趋势进行预测。预计2027年,海洋电力生产总值将达到810.3212亿元,海上风电累计装机容量将达到7016.1123万千瓦,海洋油气生产总值将达到4030.8410亿元,海洋天然气产量将达到339.1156亿立方米,表明海洋清洁能源将在能源转型中持续发挥关键作用。建议未来通过提升海洋清洁能源技术、降低海洋清洁能源成本、保障海洋清洁能源环保性以及推动海洋清洁能源发展等综合视角,全面推动海洋清洁能源健康与可持续发展。

Abstract

Since the 21st century,the development and utilization of Marine clean energy such as offshore wind power,offshore photovoltaic and Marine natural gas have made remarkable progress,becoming the key force in the green energy transformation. However,at present,Marine clean energy is also facing many opportunities and challenges. Problems such as technical bottleneck,environmental impact and sustainable use of resources limit its further development. In this context,it is of great significance to analyze and forecast the development of Marine clean energy in China. This report systematically reviews the development background and current status of marine clean energy,and establishes an ensemble model to forecast the future trends of China’s major marine clean energy sources. It is projected that by 2027,the gross output value of marine power will reach 81.03212 billion yuan,with the cumulative installed capacity of offshore wind power reaching 70.161123 million kilowatts. Additionally,the gross output value of marine oil and gas is expected to attain 40.308410 billion yuan,and marine natural gas production will reach 33.91156 billion cubic meters. These projections indicate that marine clean energy will continue to play a pivotal role in the energy transition. For the future,it is recommended to comprehensively promote the healthy and sustainable development of marine clean energy from multiple perspectives,including enhancing marine clean energy technologies,reducing costs,ensuring environmental protection,and fostering overall sector growth.

作者简介
杨文栋:杨文栋,山东财经大学管理科学与工程学院副教授,硕士生导师,研究方向为机器学习、数据挖掘、预测与评价。
张浩:张浩,山东财经大学管理科学与工程学院,研究方向为预测理论与方法。
臧欣怡:臧欣怡,山东财经大学管理科学与工程学院,研究方向为预测理论与方法。